Since the Green Revolution, worldwide agriculture has been characterized by a typical top–down approach. The degree of autonomy, creativity, and responsibility of farmers has been limited by the continuous external inputs of chemicals, machinery, advice, subsidies and knowledge. The issue of sustainability has brought complexity and uncertainty to this mainly linear process of innovation, steering agriculture toward alternative models. Agroecology represents an innovative paradigm of agriculture in which external inputs are minimized, and the assets of the farm are greatly valued.
Networks and partnerships are commonly-used tools to foster knowledge sharing between actors and organisations in the Agricultural Knowledge and Innovation System (AKIS), but in Europe the policy emphasis on including users, such as farmers and foresters, is relatively recent. This paper assesses user involvement in a diverse set of European Union (EU)-funded and non-EU (formal and informal) multi-actor partnerships. This research used a common methodology to review several forms of multi-actor partnerships involving users and other actors.
L’herbe pâturée est l’aliment qui coûte le moins cher dans une ration et la bonne gestion de l’herbe passe entre autre par une connaissance des quantités disponibles. Afin de simplifier et d’automatiser ces mesures d’herbe, et ainsi contribuer au maintien voire au développement du pâturage, le projet HERDECT s’est attaché à construire des méthodes d’estimation de la biomasse des prairies à partir d’outils de télédétection (d’acquisition à distance) et à en estimer la faisabilité opérationnelle.
La diminution du nombre de prairies, que l’on observe à l’échelle mondiale depuis plusieurs décennies, s’est accompagnée de l’évolution de leur mode de gestion dans un contexte d’intensification de l’usage des terres. Face aux enjeux que ces changements impliquent, tant sur le plan environnemental qu’économique, il est nécessaire d’identifier et de caractériser les dynamiques spatiotemporelles des prairies, afin notamment d’évaluer les impacts du changement climatique sur ces dernières et leur capacité à s’y adapter.
Le drone est un outil de plus en plus utilisé dans de nombreux domaines et en particulier en agriculture. La méthode présentée permet d’estimer la hauteur de plantes fourragères à partir de photos prises d’un drone. Cette méthode revêt un intérêt tout particulier pour la sélection végétale.
Crop surface models (CSMs) representing plant height above ground level are a useful tool for monitoring in-field crop growth variability and enabling precision agriculture applications. A semiautomated system for generating CSMs was implemented. It combines an Android application running on a set of smart cameras for image acquisition and transmission and a set of Python scripts automating the structure-from-motion (SfM) software package Agisoft Photoscan and ArcGIS. Only ground-control-point (GCP) marking was performed manually.
Innovation rests not only on discovery but also on cooperation and interactive learning. In agriculture, forestry and related sectors, multi-actor partnerships for ‘co-innovation’ occur in many forms, from international projects to informal ‘actor configurations’. Common attributes are that they include actors with ‘complementary forms of knowledge’ who collaborate in an innovation process, engage with a ‘larger periphery’ of stakeholders in the Agricultural Knowledge and Innovation System (AKIS) and are shaped by institutions.
Precision Agriculture (PA) has been advocated as a promising technology and management philosophy that provides multidimensional benefits for producers and consumers while being environmentally friendly. In Europe, private stakeholders (farm advisors, farm equipment producers, decision support providers, farmers) and research institutions have been trying to develop, test and demonstrate adoption of precision agriculture solutions with governments financing big projects in these areas. Despite these efforts, adoption is still lagging behind expectations.
Improvements in the sustainability of agricultural production depend essentially on advances in the efficient use of nitrogen. Precision farming promises solutions in this respect. Variable rate technologies allow the right quantities of fertilizer to be applied at the right place. This helps to both maintain yields and avoid nitrogen losses. However, these technologies are still not widely adopted, especially in small-scale farming systems. Recent developments in sensing technologies, like drones or satellites, open up new opportunities for variable rate technologies.
This study analyses the impact of the transfer of technological information (among other a priori identified factors) on the uptake of innovative crop technologies using structural equation modelling of data from a representative survey of Scottish crop farmers. The model explains 83% of the variance in current technological uptake behaviour and 63% of the variance in intentions to uptake new technologies.